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Tabular Imbalanced Learning: A Survey, Benchmark, and Practical Guide
Imbalanced learning remains a fundamental challenge in tabular data applications. Despite decades of research and numerous proposed methods, there is still limited systematic understanding of how different imbalance-handling strategies perform across diverse data regimes and computational constraint
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